{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring sea ice freeboards with ICESat-2 (ATL10)\n",
    "\n",
    "Information obtained primarily from the ATL07/10 Algorithm Theoretical Basis Document (ATBD, Kwok et al., 2019) and the NSIDC product description page: https://nsidc.org/data/atl10.   \n",
    "\n",
    "Notebook author: Alek Petty, relying extensively on above product manuals. \n",
    "Description: Notebook describing the ICESat-2 ATL10 product.   \n",
    "Input requirements: Demo ATL10 data file   \n",
    "Date: June 2019\n",
    "More info: See the ATL07/ATL10 Algorithm Theoretical Basis Document (ATBD): https://icesat-2.gsfc.nasa.gov/sites/default/files/page_files/ICESat2_ATL07_ATL10_ATBD_r001.pdf   \n",
    "\n",
    "\n",
    "## Notebook objectives\n",
    "* General understanding of what's included in a typical ATL10 file.\n",
    "* Plotting and basic analysis of ATL10 data.\n",
    "* Potentially some info on reading in and analyzing a large quantity of ATL10 data!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook instructions\n",
    "1. Follow along with the notebook tutorial. \n",
    "2. Play around changing options and re-running the relevant notebook cells. \n",
    "\n",
    "Here I use the hdf5 file from: https://nsidc.org/data/atl10  \n",
    "For the demo below I'm using the file: ATL10-01_20181115003141_07240101_001_01.h5   \n",
    "If using this using the ICESAT-2 Pangeo instance, you can download the file using the cell below\n",
    "\n",
    "\n",
    "### Notes      \n",
    "* Check out the known issues document: https://nsidc.org/sites/nsidc.org/files/technical-references/ATL0710-KnownIssues.pdf\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ATL10 Background\n",
    "\n",
    "ATL10 is a pretty simple product, with most of the hard work done in ATL03/07. ATL10 essentially returns the freeboard of the height segments calculated in ATL07 - the difference in height between the ice and sea surface (a mean sea surface height is calculated within 10 km along-track sections from all relevant sea surface heights for each beam). \n",
    "\n",
    "A lot of the important variables in ATL07 have been passed through to ATL10 making this a useful high-level data product of interest to the community."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Magic function to enable interactive plotting in Jupyter notebook\n",
    "#Allows you to zoom/pan within plots after generating\n",
    "#Normally, this would be %matplotlib notebook, but since we're using Juptyerlab, we need a different widget\n",
    "#%matplotlib notebook\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "#Import necesary modules\n",
    "#Use shorter names (np, pd, plt) instead of full (numpy, pandas, matplotlib.pylot) for convenience\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import pandas as pd\n",
    "import h5py\n",
    "import s3fs\n",
    "import readers as rd\n",
    "import xarray as xr\n",
    "import utils as ut\n",
    "from astropy.time import Time\n",
    "# Use seasborn for nicer looking inline plots if available \n",
    "#import seaborn as sns\n",
    "#sns.set(context='notebook', style='darkgrid')\n",
    "#st = axes_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Beam selection   \n",
    "There are 6 beams to choose from in the ICESat-2 products (3 pairs of a strong and weak beam). The energy ratio between the weak and strong beams are  approximately 1:4 and are separated by 90 m in the across-track direction. The beam pairs are separated by ~3.3 km in the across-track direction, and the strong and weak beams are separated by ~2.5 km in the along-track direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "beamStr='gt1r'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If file stored locally...\n",
    "#file_path = '../Data/'\n",
    "#ATL10file='ATL10-01_20181115003141_07240101_001_01.h5'\n",
    "#localFilePath = file_path + ATL10file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['pangeo-data-upload-oregon/icesat2/2018.nc', 'pangeo-data-upload-oregon/icesat2/2019.nc', 'pangeo-data-upload-oregon/icesat2/ATL03_20181115022655_07250104_001_01.h5', 'pangeo-data-upload-oregon/icesat2/ATL07-01_20181115003141_07240101_001_01.h5', 'pangeo-data-upload-oregon/icesat2/ATL10-01_20181115003141_07240101_001_01.h5', 'pangeo-data-upload-oregon/icesat2/NESOSIM-OSISAFsig150_ERAI_sf_SICCDR_Rhovariable_IC3_DYN1_WP1_LL1_WPF5.8e-07_WPT5_LLF2.9e-07-100kmnrt3-15082018-31012019.nc', 'pangeo-data-upload-oregon/icesat2/readme.txt', 'pangeo-data-upload-oregon/icesat2/Clouds_and_filtering_tutorial', 'pangeo-data-upload-oregon/icesat2/Floes-are-Swell', 'pangeo-data-upload-oregon/icesat2/NSIDC_0081', 'pangeo-data-upload-oregon/icesat2/Snowblower', 'pangeo-data-upload-oregon/icesat2/atl03', 'pangeo-data-upload-oregon/icesat2/atl06', 'pangeo-data-upload-oregon/icesat2/atl10', 'pangeo-data-upload-oregon/icesat2/atl12', 'pangeo-data-upload-oregon/icesat2/data-access-outputs', 'pangeo-data-upload-oregon/icesat2/data-access-shapefile', 'pangeo-data-upload-oregon/icesat2/data-access-subsetted-outputs', 'pangeo-data-upload-oregon/icesat2/data-access-subsettedoutputs', 'pangeo-data-upload-oregon/icesat2/data-correction', 'pangeo-data-upload-oregon/icesat2/eds_files', 'pangeo-data-upload-oregon/icesat2/elevation_change_tutorial', 'pangeo-data-upload-oregon/icesat2/geospatial-analysis', 'pangeo-data-upload-oregon/icesat2/glaciersat2', 'pangeo-data-upload-oregon/icesat2/gridding-data', 'pangeo-data-upload-oregon/icesat2/ground2float', 'pangeo-data-upload-oregon/icesat2/juneauicefield', 'pangeo-data-upload-oregon/icesat2/pine_island_glims', 'pangeo-data-upload-oregon/icesat2/segtrax', 'pangeo-data-upload-oregon/icesat2/xtrak']\n"
     ]
    }
   ],
   "source": [
    "# If running on Pangeo instance and grabbing data from Amazon S3\n",
    "bucket = 'pangeo-data-upload-oregon'\n",
    "fs = s3fs.S3FileSystem()\n",
    "dataDir = 'pangeo-data-upload-oregon/icesat2/'\n",
    "s3List = fs.ls(dataDir)\n",
    "print(s3List)\n",
    "ATL10file='ATL10-01_20181115003141_07240101_001_01.h5'\n",
    "s3File='pangeo-data-upload-oregon/icesat2/'+ATL10file\n",
    "localFilePath='../Data/'+ATL10file\n",
    "#fs.get(s3File, localFilePath)\n",
    "\n",
    "# If you want to upload data you can do so using this command: aws s3 cp ATL10-01_20181115003141_07240101_001_01.h5 s3://pangeo-data-upload-oregon/icesat2/ATL10-01_20181115003141_07240101_001_01.h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getATL10data(fileT, beam='gt1r', maxFreeboard=10):\n",
    "    \"\"\" Pandas/numpy ATL10 reader\n",
    "    Written by Alek Petty, June 2018 (alek.a.petty@nasa.gov)\n",
    "\n",
    "\tI've picked out the variables from ATL10 I think are of most interest to sea ice users, \n",
    "    but by no means is this an exhastive list. \n",
    "    See the xarray or dictionary readers to load in the more complete ATL10 dataset\n",
    "    or explore the hdf5 files themselves (I like using the app Panpoly for this) to see what else you might want\n",
    "    \n",
    "\tArgs:\n",
    "\t\tfileT (str): File path of the ATL10 dataset\n",
    "\t\tbeamStr (str): ICESat-2 beam (the number is the pair, r=strong, l=weak)\n",
    "        maxFreeboard (float): maximum freeboard (meters)\n",
    "\n",
    "\treturns:\n",
    "        pandas dataframe\n",
    "\n",
    "\t\"\"\"\n",
    "\n",
    "    print('ATL10 file:', fileT)\n",
    "    \n",
    "    f1 = h5py.File(fileT, 'r')\n",
    "    \n",
    "    freeboard=f1[beam]['freeboard_beam_segment']['beam_freeboard']['beam_fb_height'][:]\n",
    "\n",
    "    freeboard_confidence=f1[beam]['freeboard_beam_segment']['beam_freeboard']['beam_fb_confidence'][:]\n",
    "    freeboard_quality=f1[beam]['freeboard_beam_segment']['beam_freeboard']['beam_fb_quality_flag'][:]\n",
    "    \n",
    "    # Delta time in gps seconds\n",
    "    delta_time = f1[beam]['freeboard_beam_segment']['beam_freeboard']['delta_time'][:]\n",
    "    # Height segment ID (10 km segments)\n",
    "    height_segment_id=f1[beam]['freeboard_beam_segment']['beam_freeboard']['height_segment_id'][:]\n",
    "    \n",
    "    lons=f1[beam]['freeboard_beam_segment']['beam_freeboard']['longitude'][:]\n",
    "    lats=f1[beam]['freeboard_beam_segment']['beam_freeboard']['latitude'][:]\n",
    "    deltaTimeRel=delta_time-delta_time[0]\n",
    "    \n",
    "    # #Add this value to delta time parameters to compute full gps_seconds\n",
    "    atlas_epoch=f1['/ancillary_data/atlas_sdp_gps_epoch'][:] \n",
    "    \n",
    "    leapSecondsOffset=37\n",
    "    gps_seconds = atlas_epoch[0] + delta_time - leapSecondsOffset\n",
    "    # Use astropy to convert from gps time to datetime\n",
    "    tgps = Time(gps_seconds, format='gps')\n",
    "    tiso = Time(tgps, format='datetime')\n",
    "    tiso\n",
    "    # Conversion of delta_time to a calendar date\n",
    "    #temp = ut.convert_GPS_time(atlas_epoch[0] + deltaTime, OFFSET=0.0)\n",
    "    \n",
    "    \n",
    "    #year = temp['year'][:].astype('int')\n",
    "    #month = temp['month'][:].astype('int')\n",
    "    #day = temp['day'][:].astype('int')\n",
    "    #hour = temp['hour'][:].astype('int')\n",
    "    #minute = temp['minute'][:].astype('int')\n",
    "    #second = temp['second'][:].astype('int')\n",
    "    #dFtime=pd.DataFrame({'year':year, 'month':month, 'day':day, \n",
    "    #                    'hour':hour, 'minute':minute, 'second':second})\n",
    "    \n",
    "\n",
    "    dF = pd.DataFrame({'freeboard':freeboard, 'lon':lons, 'lat':lats, 'deltaTimeRel':deltaTimeRel, \n",
    "                     'height_segment_id':height_segment_id,'datetime': tiso})\n",
    "    \n",
    "    def getMonth(x):\n",
    "        return x.to_datetime().month\n",
    "\n",
    "    dF['months'] = dF['datetime'].apply(getMonth)\n",
    "    \n",
    "    #dF['months'] = pd.Series(months, index=dF.index)\n",
    "    dF = dF[(dF['freeboard']>0)]\n",
    "    dF = dF[(dF['freeboard']<maxFreeboard)]\n",
    "    # Decide here if we want to also filter based on the confidence and/or quality flag\n",
    "    \n",
    "    # Reset row indexing\n",
    "    dF=dF.reset_index(drop=True)\n",
    "\n",
    "    return dF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Read in the data using the pandas reader above. Copied from the readers.py script.\n",
    "\n",
    "Take a look at the top few rows (change the number in head to increase this..)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ATL10 file: ../Data/ATL10-01_20181115003141_07240101_001_01.h5\n"
     ]
    }
   ],
   "source": [
    "dF10 = getATL10data(localFilePath, beam=beamStr)\n",
    "dF10.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Map the data for visual inspection using Cartopy \n",
    "*NB (Basemap is often used for mapping but is not being officially supported by the community anymore)*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 630x630 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "var='freeboard'\n",
    "plt.figure(figsize=(7,7), dpi= 90)\n",
    "# Make a new projection \"NorthPolarStereo\"\n",
    "# ccrs.PlateCarree\n",
    "ax = plt.axes(projection=ccrs.NorthPolarStereo(true_scale_latitude=70))\n",
    "plt.scatter(dF10['lon'], dF10['lat'],c=dF10[var], cmap='viridis', vmin=0, vmax=0.3, transform=ccrs.PlateCarree())\n",
    "#plt.pcolormesh(lons, lats, tile_to_plot,\n",
    "#               transform=ccrs.PlateCarree());\n",
    "\n",
    "ax.coastlines()\n",
    "#ax.drawmeridians()\n",
    "plt.colorbar(label=var, shrink=0.5, extend='both')\n",
    "\n",
    "# Limit the map to -60 degrees latitude and below.\n",
    "ax.set_extent([-180, 180, 90, 60], ccrs.PlateCarree())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Apply Warren snow depth and density data \n",
    "Below function adds data from function fits for the given time/location of each freeboard point\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>freeboard</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>delta_time</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>datetime</th>\n",
       "      <th>snowDepthW99</th>\n",
       "      <th>snowDensityW99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.092154</td>\n",
       "      <td>-168.648556</td>\n",
       "      <td>73.745906</td>\n",
       "      <td>219.501606</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227908</td>\n",
       "      <td>299.872994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.054907</td>\n",
       "      <td>-168.648610</td>\n",
       "      <td>73.746011</td>\n",
       "      <td>219.503267</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.043049</td>\n",
       "      <td>-168.648625</td>\n",
       "      <td>73.746040</td>\n",
       "      <td>219.503734</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.024505</td>\n",
       "      <td>-168.648647</td>\n",
       "      <td>73.746084</td>\n",
       "      <td>219.504422</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.004605</td>\n",
       "      <td>-168.648697</td>\n",
       "      <td>73.746182</td>\n",
       "      <td>219.505991</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227910</td>\n",
       "      <td>299.873698</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   freeboard         lon        lat  delta_time  year  month  day  \\\n",
       "0   0.092154 -168.648556  73.745906  219.501606  2018      1    1   \n",
       "1   0.054907 -168.648610  73.746011  219.503267  2018      1    1   \n",
       "2   0.043049 -168.648625  73.746040  219.503734  2018      1    1   \n",
       "3   0.024505 -168.648647  73.746084  219.504422  2018      1    1   \n",
       "4   0.004605 -168.648697  73.746182  219.505991  2018      1    1   \n",
       "\n",
       "             datetime  snowDepthW99  snowDensityW99  \n",
       "0 2018-01-01 00:03:39      0.227908      299.872994  \n",
       "1 2018-01-01 00:03:39      0.227909      299.873261  \n",
       "2 2018-01-01 00:03:39      0.227909      299.873336  \n",
       "3 2018-01-01 00:03:39      0.227909      299.873446  \n",
       "4 2018-01-01 00:03:39      0.227910      299.873698  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add this to the dataframe\n",
    "dF10=ut.getWarrenData(dF10, 'snowDepthW99', outDensityVar='snowDensityW99')\n",
    "dF10.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert to thickness using the Warren snow depth/density..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>freeboard</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>delta_time</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>datetime</th>\n",
       "      <th>snowDepthW99</th>\n",
       "      <th>snowDensityW99</th>\n",
       "      <th>iceThickness</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.092154</td>\n",
       "      <td>-168.648556</td>\n",
       "      <td>73.745906</td>\n",
       "      <td>219.501606</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227908</td>\n",
       "      <td>299.872994</td>\n",
       "      <td>0.279136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.054907</td>\n",
       "      <td>-168.648610</td>\n",
       "      <td>73.746011</td>\n",
       "      <td>219.503267</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873261</td>\n",
       "      <td>0.166315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.043049</td>\n",
       "      <td>-168.648625</td>\n",
       "      <td>73.746040</td>\n",
       "      <td>219.503734</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873336</td>\n",
       "      <td>0.130395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.024505</td>\n",
       "      <td>-168.648647</td>\n",
       "      <td>73.746084</td>\n",
       "      <td>219.504422</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227909</td>\n",
       "      <td>299.873446</td>\n",
       "      <td>0.074226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.004605</td>\n",
       "      <td>-168.648697</td>\n",
       "      <td>73.746182</td>\n",
       "      <td>219.505991</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2018-01-01 00:03:39</td>\n",
       "      <td>0.227910</td>\n",
       "      <td>299.873698</td>\n",
       "      <td>0.013949</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   freeboard         lon        lat  delta_time  year  month  day  \\\n",
       "0   0.092154 -168.648556  73.745906  219.501606  2018      1    1   \n",
       "1   0.054907 -168.648610  73.746011  219.503267  2018      1    1   \n",
       "2   0.043049 -168.648625  73.746040  219.503734  2018      1    1   \n",
       "3   0.024505 -168.648647  73.746084  219.504422  2018      1    1   \n",
       "4   0.004605 -168.648697  73.746182  219.505991  2018      1    1   \n",
       "\n",
       "             datetime  snowDepthW99  snowDensityW99  iceThickness  \n",
       "0 2018-01-01 00:03:39      0.227908      299.872994      0.279136  \n",
       "1 2018-01-01 00:03:39      0.227909      299.873261      0.166315  \n",
       "2 2018-01-01 00:03:39      0.227909      299.873336      0.130395  \n",
       "3 2018-01-01 00:03:39      0.227909      299.873446      0.074226  \n",
       "4 2018-01-01 00:03:39      0.227910      299.873698      0.013949  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dF10=ut.getSnowandConverttoThickness(dF10, snowDepthVar='snowDepthW99', \n",
    "                                 snowDensityVar='snowDensityW99',\n",
    "                                 outVar='iceThickness')\n",
    "dF10.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 630x630 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Map the data for visual inspection usign Cartopy\n",
    "var='iceThickness'\n",
    "plt.figure(figsize=(7,7), dpi= 90)\n",
    "# Make a new projection \"NorthPolarStereo\"\n",
    "ax = plt.axes(projection=ccrs.NorthPolarStereo(true_scale_latitude=70))\n",
    "plt.scatter(dF10['lon'], dF10['lat'],c=dF10[var], cmap='viridis', vmin=0, vmax=1, transform=ccrs.PlateCarree())\n",
    "#plt.pcolormesh(lons, lats, tile_to_plot,\n",
    "#               transform=ccrs.PlateCarree());\n",
    "\n",
    "ax.coastlines()\n",
    "#ax.drawmeridians()\n",
    "plt.colorbar(label=var, shrink=0.5, extend='both')\n",
    "\n",
    "# Limit the map to -60 degrees latitude and below.\n",
    "ax.set_extent([-180, 180, 90, 60], ccrs.PlateCarree())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extra ideas\n",
    "\n",
    "1. Check beam consistency!\n",
    "2. Look at the high-res thickness distribution. How do the histograms look?\n",
    "3. Add your favourite (clearly NESOSIM) snow depth and density data and assess thicknesses. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### As part of the project science office activities we've been producing a semi-official sea ice thickness product using ATL10 and snow loading from the NESOSIM snow model\n",
    "\n",
    "You can access one week of November high-res thickness data here: https://drive.google.com/file/d/1tN3qL0rBq2r1mJT00VFB9hQpHASKq7C5/view?usp=sharing   \n",
    "\n",
    "I have provided a batch reader function for this data in utils.py: getProcessedATL10ShotdataNCDF so I encourage you to use that and try and generate some thickness plots.   \n",
    "\n",
    "The thickness data include various estimates based on different uses of the snow loading (products and redistribution). This is still work in progress so I can't provide too mnay more official details yet!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:root] *",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
